ML Engineer, Apple Foundation Models
Core
Develop data strategies, pipelines, and methodologies to drive capability in Apple's frontier foundation models across the full training lifecycle.
Role type
Senior IC machine-learning engineer (data-centric foundation models)
Builds
Scalable data generation, curation, and quality assessment systems for text, multimodal, reasoning, and agentic training data
Domain
Artificial Intelligence / Large Language Models / Data Engineering
Deliverable
production ML models
Required skills
LLM or Multi-modal LLM expertise, Python programming, deep learning toolkits (JAX, PyTorch, Tensorflow), data strategy design, synthetic data generation, benchmark-driven optimization, reward modeling, model self-evolution frameworks
Preferred skills
Large-scale data flywheels experience, agentic systems and tool-use capabilities, multimodal foundation model development, model self-improvement techniques, user interaction data integration
Technologies
JAX, PyTorch, Tensorflow
Responsibilities
Drive data strategy and mixture design across pre-training, mid-training, and post-training; Design and build scalable data generation and quality assessment systems; Develop synthetic data pipelines for complex capabilities; Create model self-improvement and self-iteration frameworks; Pioneer data flywheels for continual capability advancement; Develop benchmark-driven methodologies to identify capability gaps; Advance state-of-the-art techniques in data-centric AI including reward modeling and preference learning
Seniority
Senior, hands-on IC
